A new phase in DEB research

Augustine, Starrlight; Kooijman, S.A.L.M.

doi:10.1016/j.seares.2018.06.003

Cited by 13 publications

(9 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, they provide an easy first-cut approach in estimating performance based on body temperature. More sophisticated approaches could, for example, alter the spatial distribution of individual TPCs of animals based on their thermal history (Kingsolver and Woods, 2016) or could use physiological approaches such as Dynamic Energy Budget models that explicitly account for thermal history (Augustine and Kooijman, 2019).…”

Section: Spatial Model Frameworkmentioning

confidence: 99%

Mapping physiology: biophysical mechanisms define scales of climate change impacts

Choi

Gouhier

Lima

et al. 2019

Conservation Physiology

View full text Add to dashboard Cite

The rocky intertidal zone is a highly dynamic and thermally variable ecosystem, where the combined influences of solar radiation, air temperature and topography can lead to differences greater than 15°C over the scale of centimetres during aerial exposure at low tide. For most intertidal organisms this small-scale heterogeneity in microclimates can have enormous influences on survival and physiological performance. However, the potential ecological importance of environmental heterogeneity in determining ecological responses to climate change remains poorly understood. We present a novel framework for generating spatially explicit models of microclimate heterogeneity and patterns of thermal physiology among interacting organisms. We used drone photogrammetry to create a topographic map (digital elevation model) at a resolution of 2 × 2 cm from an intertidal site in Massachusetts, which was then fed into to a model of incident solar radiation based on sky view factor and solar position. These data were in turn used to drive a heat budget model that estimated hourly surface temperatures over the course of a year (2017). Body temperature layers were then converted to thermal performance layers for organisms, using thermal performance curves, creating ‘physiological landscapes’ that display spatially and temporally explicit patterns of ‘microrefugia’. Our framework shows how non-linear interactions between these layers lead to predictions about organismal performance and survivorship that are distinct from those made using any individual layer (e.g. topography, temperature) alone. We propose a new metric for quantifying the ‘thermal roughness’ of a site (RqT, the root mean square of spatial deviations in temperature), which can be used to quantify spatial and temporal variability in temperature and performance at the site level. These methods facilitate an exploration of the role of micro-topographic variability in driving organismal vulnerability to environmental change using both spatially explicit and frequency-based approaches.

show abstract

Section: Spatial Model Frameworkmentioning

confidence: 99%

Mapping physiology: biophysical mechanisms define scales of climate change impacts

Choi

Gouhier

Lima

et al. 2019

Conservation Physiology

View full text Add to dashboard Cite

show abstract

“…Alternatively, the DEB approach has been calibrated and validated for multiple estuaries in the Gulf of Mexico, such that this on-reef approach to modeling oyster growth and reproduction provides a similarly flexible option to the size-structured model for coupling with larval transport models to evaluate the full oyster life cycle by estuary. The DEB model provides a mechanistic (processbased) approach, based on physiological and metabolic processes common to all living species, that can be easily adapted to both genetic variation in natural populations and variation in local environmental conditions (Augustine and Kooijman, 2019), and may be easily adapted across the wide range of conditions in Gulf of Mexico estuaries.…”

Section: Discussionmentioning

confidence: 99%

Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters

Peyre¹,

Marshall²,

Sable³

2021

Open-File Report

View full text Add to dashboard Cite

show abstract

“…The parameter sets are freely available [ 26 ], and can be used in combination with a well-tested Matlab code that has frequently been used (see, e.g. the recent 6th special issue on DEB theory, [ 27 ]). A detailed description of the DEB model can be found in Additional file 1 .…”

Section: Methodsmentioning

confidence: 99%

Modelling effects of time-variable exposure to the pyrethroid beta-cyfluthrin on rainbow trout early life stages

Zimmer¹,

Preuß

Norman³

et al. 2018

Environ Sci Eur

View full text Add to dashboard Cite

BackgroundAvailable literature and regulatory studies show that the severity of effects of beta-cyfluthrin (a synthetic pyrethroid) on fish is influenced by the magnitude and duration of exposure. To investigate how the exposure pattern to beta-cyfluthrin (constant vs peak) may influence the response of the fish, we used a mechanistic effect model to predict the survival and growth of the rainbow trout over its early life stages (i.e. egg, alevin and swim-up fry). We parameterized a toxicokinetic–toxicodynamic (TKTD) module in combination with a dynamic energy budget model enabling us to describe uptake and elimination, as well as to predict the threshold concentration for survival and sublethal effects (feeding behaviour and growth). This effect model was calibrated using data from an early life stage experiment where trout was exposed to a constant concentration of cyfluthrin. The model was validated by comparing model predictions to independent data from a pulsed-exposure study with early life stages of rainbow trout.ResultsThe co-occurrence of effects on behaviour and growth raised the possibility that these were interrelated, i.e. impairment of feeding behaviour may have led to reduced food intake and slower growth. We, therefore, included ‘effect on feeding’ as mode of action in the TKTD module. At higher concentrations, the constant exposure led to death. The model was able to adequately capture this effect pattern in the calibration. The model was able to adequately predict the response of fish eggs, alevins and swim-up fry, from both the qualitative (response pattern) and quantitative points of view.ConclusionsSince the model was successfully validated, it can be used to predict survival and growth of early life stages under various realistic time-variable exposure profiles (e.g. profiles from FOCUS surface water modelling) of beta-cyfluthrin.Electronic supplementary materialThe online version of this article (10.1186/s12302-018-0162-0) contains supplementary material, which is available to authorized users.

show abstract

A new phase in DEB research

Cited by 13 publications

References 37 publications

Mapping physiology: biophysical mechanisms define scales of climate change impacts

Mapping physiology: biophysical mechanisms define scales of climate change impacts

Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters

Modelling effects of time-variable exposure to the pyrethroid beta-cyfluthrin on rainbow trout early life stages

Contact Info

Product

Resources

About